地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (7): 1286-1300.doi: 10.12082/dqxxkx.2022.210823
裴泽华1(), 葛淼1,*(
), 李浩1, 何进伟2, 王聪霞3
收稿日期:
2021-12-22
修回日期:
2022-03-22
出版日期:
2022-07-25
发布日期:
2022-09-25
通讯作者:
* 葛 淼(1960—),男,陕西咸阳人,教授,主要从事健康地理研究。E-mail: gemiao@snnu.edu.cn作者简介:
裴泽华(1997—),男,山西长治人,硕士生,主要从事健康地理研究。E-mail: pzh15635445598@163.com
基金资助:
PEI Zehua1(), GE Miao1,*(
), LI Hao1, HE Jinwei2, WANG Congxia3
Received:
2021-12-22
Revised:
2022-03-22
Online:
2022-07-25
Published:
2022-09-25
Contact:
GE Miao
Supported by:
摘要:
高密度脂蛋白胆固醇(HDL-C)可以有效促进人体内胆固醇的代谢外排,其水平的高低与患心血管疾病的风险呈负相关关系,是心血管疾病的预防与保护因素。厘清我国中老年人群HDL-C水平的地理分异特征及环境影响因素,对我国心血管疾病防治工作的开展有重要意义。论文基于中国中老年人纵向追踪调查,利用全局空间自相关、冷热点分析等方法阐释中国中老年人群HDL-C水平的空间分异特征及变化趋势,同时对比引入随机森林回归模型及多元线性回归方法探讨HDL-C水平空间分布的环境影响因素及其指示作用。结果表明:中国中老年人群HDL-C水平表现为女性高于男性、农村高于城镇,具有明显的地域差异性,整体呈现出“北低南高,中间过渡”的分布格局,且北方出现了以内蒙古、河北、辽宁为代表的低值聚集区,南方出现了以广东、广西、云南为代表的高值聚集区;SO2、NO2、降水、气压、PM10和PM2.5是影响中老年人群HDL-C水平差异分布的主要环境因素,其中高浓度的空气污染物是造成HDL-C值较低的危险因素,充沛的降水和低压环境是防治HDL-C值较低的保护因素。因此,今后关于HDL-C血脂异常防控工作在全国各地应注重其空间分布规律,重点加强对HDL-C低值区的监测,以达到因地制宜、精准防控的目的。
裴泽华, 葛淼, 李浩, 何进伟, 王聪霞. 基于随机森林模型的中国中老年人群HDL-C环境影响因素研究[J]. 地球信息科学学报, 2022, 24(7): 1286-1300.DOI:10.12082/dqxxkx.2022.210823
PEI Zehua, GE Miao, LI Hao, HE Jinwei, WANG Congxia. Environmental Factors Influencing HDL-C in Middle-aged and Elderly Chinese Population based on Random Forest Model[J]. Journal of Geo-information Science, 2022, 24(7): 1286-1300.DOI:10.12082/dqxxkx.2022.210823
表1
普通克里金插值半变异函数及交叉验证精度指标
影响因素 | 半变异函数 | 平均绝对误差 | 均方根误差RMSE | 平均相对误差 |
---|---|---|---|---|
气压 | 高斯模型 | 24.024 | 35.892 | 2.869 |
气温 | 高斯模型 | 1.339 | 2.196 | 28.889 |
湿度 | 高斯模型 | 3.746 | 5.012 | 6.546 |
降水 | 高斯模型 | 134.555 | 196.567 | 24.883 |
NO2 | 指数模型 | 6.015 | 7.794 | 24.571 |
SO2 | 指数模型 | 5.445 | 7.866 | 26.013 |
CO | 指数模型 | 0.167 | 0.228 | 17.251 |
O3 | 指数模型 | 10.399 | 13.838 | 11.603 |
PM2.5 | 指数模型 | 4.644 | 6.367 | 10.205 |
PM10 | 指数模型 | 8.331 | 11.751 | 10.908 |
表2
HDL-C调查人群的性别及城乡类型基本特征
年份 | 人数/人 | 城乡类型 | 性别/(mg/dl) | 差值/(mg/dl) | 合计/(mg/dl) |
---|---|---|---|---|---|
2011年 | 11 663 | 合计 | 男:50.34±16.25 | 0.94 | 50.84±15.32 |
女:51.28±14.47 | |||||
城镇 | 男:47.52±15.58 | 1.93 | 48.58±14.72 | ||
女:49.45±13.91 | |||||
农村 | 男:51.92±16.40 | 0.46 | 52.16±15.52 | ||
女:52.38±14.69 | |||||
2015年 | 13 354 | 合计 | 男:49.97±12.32 | 2.22 | 51.17±11.52 |
女:52.19±10.70 | |||||
城镇 | 男:48.20±11.18 | 3.04 | 49.87±10.77 | ||
女:51.24±10.22 | |||||
农村 | 男:51.01±12.83 | 1.79 | 51.97±11.90 | ||
女:52.80±10.94 |
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